Various types of systems are well known for determining and tracking the positions of a plurality of spatially distributed remote objects or targets. One typical application of such systems is in tracking aircraft which may be considered "targets" in a warfare environment. The problem of tracking target aircraft is complicated by modern electronic counter measures (ECM) in which the aircraft have the ability to jam radars via broadband noise jamming. As a result of jamming, the radar is denied range information, thus rendering a single radar useless for tracking the target.
Others in the past have employed passive tracking techniques using networks of sensors such as sonar and radar. However, in each case, the system assumes that additional information is available, such as the frequency of the emissions, which is used in the tracking process. The additional information is used for the correlation of data received by the different sensors as a discriminant of distinct targets. This approach is undesirable in that it results in higher loads on communication links and more complicated signal processing. Moreover, the performance of such systems will be degraded as more sophisticated emitters are developed from which the sensors cannot discriminate one emitter from another.
There are two primary problems associated with position estimation of multiple targets using multiple sensors. The first is the inaccuracy of sensor measurements and the second is the uncertainty of the origin of those measurements. These problems are particularly acute with angle (bearing-only) sensors (such as jammed radar or infrared sensors) where the measurement consists of the angle (azimuth and possibly elevation) from the target to the sensor. Thus, a single sensor cannot provide complete spatial information about the target but can only determine that the target lies on a line-of-bearing. With the additional measurements from a second sensor, the location of the target can be determined as the intersection of the two lines of bearing. However, in a multiple target environment, multiple lines of bearings will be detected at both sensors. Bearing lines will cross and intersections are formed at points where targets do not actually exist. These points of intersections are sometimes referred to as "ghosts". To illustrate the severity of the problem, if ten targets are observed at both sensors, up to 100 intersections can be formed so that up to 90 ghosts appear. If the sensors have no other information available, no further discrimination of targets from ghosts can be made.
The present invention involves, in part, recognition of the fact that the use of a third sensor will help resolve the target ambiguities, since the targets will be located at the intersections of three lines of bearing. However, ghosts could still occur with three sensors, though this is unlikely if the sensor measurements are perfect. In reality, however, sensor measurement inaccuracies are experienced and the three lines of bearing corresponding to a true target will not intersect at a single point, but rather will define a triangular region. For many target scenarios, there may be many triangular regions; some of these regions correspond to true targets but many correspond to ghosts. The apparent target positions can be estimated using standard statistical techniques and any three lines of bearing, yet it will not be known whether a true target or a ghost is present.
The present invention discloses a method for resolving the ambiguities mentioned above so that true targets can be distinguished from ghosts.